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To select or to combine? The inventory performance of model and expert forecasts

Wang, Xun ORCID: https://orcid.org/0000-0001-7800-726X and Petropoulos, Fotios 2016. To select or to combine? The inventory performance of model and expert forecasts. International Journal of Production Research 54 (17) , pp. 5271-5282. 10.1080/00207543.2016.1167983

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Abstract

Demand forecasting is a crucial input of any inventory system. The quality of the forecasts should be evaluated not only in terms of forecast accuracy or bias but also with regards to their inventory implications, which include the impact on the total inventory cost, the achieved service levels and the variance of orders and inventory. Forecast selection and combination are two very widely applied forecasting strategies that have shown repeatedly to increase the forecasting performance. However, the inventory performance of these strategies remains unexplored. We empirically examine the effects of forecast selection and combination on inventory when two sources of forecasts are available. We employ a large data-set that contains demands and (statistical and judgmental) forecasts for multiple pharmaceutical stock keeping units. We show that forecast selection and simple combination increase simultaneously the forecasting and inventory performance.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > HD Industries. Land use. Labor
Publisher: Taylor & Francis
ISSN: 0020-7543
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 10 March 2016
Last Modified: 05 May 2023 17:52
URI: https://orca.cardiff.ac.uk/id/eprint/87724

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